As leading AI models ace familiar tests, researchers warn that conventional benchmarks are losing their edge. A new multidisciplinary, expert-level exam curated by an academic–industry consortium aims to reset the bar, probing reasoning and deep knowledge across domains and making it harder for systems like ChatGPT and Gemini to skate by on pattern match. The authors argue that carefully sourced questions and tighter controls on data leakage are essential to distinguish real progress from overfitting. The push reflects a broader shift: in the race to build smarter AI, how we measure intelligence is becoming as critical as the models themselves.
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